## 1. Inferring Functions

Consider our model of function inference from the chapter:

///fold:
// make expressions easier to look at
var prettify = function(e) {
if (e == 'x' || _.isNumber(e)) {
return e
} else {
var op = e[0]
var arg1 = prettify(e[1])
var prettyarg1 = (!_.isArray(e[1]) ? arg1 : '(' + arg1 + ')')
var arg2 = prettify(e[2])
var prettyarg2 = (!_.isArray(e[2]) ? arg2 : '(' + arg2 + ')')
return prettyarg1 + ' ' + op + ' ' + prettyarg2
}
}

var plus = function(a,b) {
return a + b;
}

var multiply = function(a,b) {
return Math.round(a * b,0);
}

var divide = function(a,b) {
return Math.round(a/b,0);
}

var minus = function(a,b) {
return a - b;
}

var power = function(a,b) {
return Math.pow(a,b);
}

// make expressions runnable
var runify = function(e) {
if (e == 'x') {
return function(z) { return z }
} else if (_.isNumber(e)) {
return function(z) { return e }
} else {
var op = (e[0] == '+') ? plus :
(e[0] == '-') ? minus :
(e[0] == '*') ? multiply :
(e[0] == '/') ? divide :
power;
var arg1Fn = runify(e[1])
var arg2Fn = runify(e[2])
return function(z) {
return op(arg1Fn(z),arg2Fn(z))
}
}
}

var randomConstantFunction = function() {
return uniformDraw(_.range(10))
}

var randomCombination = function(f,g) {
var op = uniformDraw(['+','-','*','/','^']);
return [op, f, g];
}

// sample an arithmetic expression
var randomArithmeticExpression = function() {
if (flip(0.3)) {
return randomCombination(randomArithmeticExpression(), randomArithmeticExpression())
} else {
if (flip()) {
return 'x'
} else {
return randomConstantFunction()
}
}
}
///

viz.table(Infer({method: 'enumerate', maxExecutions: 100}, function() {
var e = randomArithmeticExpression();
var s = prettify(e);
var f = runify(e);

condition(f(0) == 0)
condition(f(2) == 4)

return {s: s};
}))


Why does this think the probability of x * 2 is so much lower than x * x?

HINT: Think about the probability assigned to x ^ 2.

#### b)

Letâ€™s reconceptualize of our program as a sequence-generator. Suppose that the first number in the sequence ($f(1)$) is 1 and the second number ($f(2)$) is 4. What number comes next?

///fold:
// make expressions easier to look at
var prettify = function(e) {
if (e == 'x' || _.isNumber(e)) {
return e
} else {
var op = e[0]
var arg1 = prettify(e[1])
var prettyarg1 = (!_.isArray(e[1]) ? arg1 : '(' + arg1 + ')')
var arg2 = prettify(e[2])
var prettyarg2 = (!_.isArray(e[2]) ? arg2 : '(' + arg2 + ')')
return prettyarg1 + ' ' + op + ' ' + prettyarg2
}
}

var plus = function(a,b) {
return a + b;
}

var multiply = function(a,b) {
return Math.round(a * b,0);
}

var divide = function(a,b) {
return Math.round(a/b,0);
}

var minus = function(a,b) {
return a - b;
}

var power = function(a,b) {
return Math.pow(a,b);
}

// make expressions runnable
var runify = function(e) {
if (e == 'x') {
return function(z) { return z }
} else if (_.isNumber(e)) {
return function(z) { return e }
} else {
var op = (e[0] == '+') ? plus :
(e[0] == '-') ? minus :
(e[0] == '*') ? multiply :
(e[0] == '/') ? divide :
power;
var arg1Fn = runify(e[1])
var arg2Fn = runify(e[2])
return function(z) {
return op(arg1Fn(z),arg2Fn(z))
}
}
}

var randomConstantFunction = function() {
return uniformDraw(_.range(10))
}

var randomCombination = function(f,g) {
var op = uniformDraw(['+','-','*','/','^']);
return [op, f, g];
}

// sample an arithmetic expression
var randomArithmeticExpression = function() {
if (flip(0.3)) {
return randomCombination(randomArithmeticExpression(), randomArithmeticExpression())
} else {
if (flip()) {
return 'x'
} else {
return randomConstantFunction()
}
}
}
///

viz.table(Infer({method: 'enumerate', maxExecutions: 10000}, function() {
var e = randomArithmeticExpression();
var s = prettify(e);
var f = runify(e);

condition(f(1) == 1)
condition(f(2) == 4)

return {'f(3)':f(3)};
}))


Not surprisingly, the model predicts 9 as the most likely next number. However, it also puts significant probability on 27. Why does this happen?

#### c)

Many people find the high probability assignmed by our model in (b) to 27 to be unintuitive. This suggests our model is an imperfect model of human intuitions. How could we decrease the probability of inferring 27? (HINT: Consider the priors).